In this paper we consider the setting of graph-structured data that evolves as a result of operations carried out by users or applications. We study different reasoning problems, which range from ensuring the satisfaction of a given set of integrity constraints after a given sequence of updates, to deciding the (non-)existence of a sequence of actions that would take the data to an (un)desirable state, starting either from a specific data instance or from an incomplete description of it. We consider a simple action language in which actions are finite sequences of insertions and deletions of nodes and labels, and use Description Logics for describing integrity constraints and (partial) states of the data. We then formalize the data management problems mentioned above as a static verification problem and several planning problems. We provide algorithms and tight complexity bounds for the formalized problems, both for an expressive DL and for a variant of DL-Lite.

Instance checking is considered a central service for data retrieval from description logic (DL) ontologies. In this paper, we propose a revised most specific concept (MSC) method for DL SHI}, which converts instance checking into subsumption problems. This revised method can generate small concepts that are specific-enough to answer a given query, and allow reasoning to explore only a subset of the ABox data to achieve efficiency. Experiments show effectiveness of our proposed method in terms of concept size reduction and the improvement in reasoning efficiency.

The action programming language GOLOG has been found useful for the control of autonomous agents such as mobile robots. In scenarios like these, tasks are often open-ended so that the respective control programs are non-terminating. Before deploying such programs on a robot, it is often desirable to verify that they meet certain requirements. For this purpose, Claßen and Lakemeyer recently introduced algorithms for the verification of temporal properties of GOLOG programs. However, given the expressiveness of GOLOG, their verification procedures are not guaranteed to terminate. In this paper, we show how decidability can be obtained by suitably restricting the underlying base logic, the effect axioms for primitive actions, and the use of actions within GOLOG programs. Moreover, we show that dropping any of these restrictions immediately leads to undecidability of the verification problem.

Recently several inconsistency-tolerant semantics have been introduced for querying inconsistent description logic knowledge bases. Most of these semantics rely on the notion of a repair, defined as an inclusion-maximal subset of the facts (ABox) which is consistent with the ontology (TBox). In this paper, we study variants of two popular inconsistency-tolerant semantics obtained by replacing classical repairs by various types of preferred repair. We analyze the complexity of query answering under the resulting semantics, focusing on the lightweight logic DL-Lite_R. Unsurprisingly, query answering is intractable in all cases, but we nonetheless identify one notion of preferred repair, based upon priority levels, whose data complexity is "only" coNP-complete. This leads us to propose an approach combining incomplete tractable methods with calls to a SAT solver. An experimental evaluation of the approach shows good scalability on realistic cases.

Nominal schemas extend description logics (DLs) with a restricted form of variables, thus integrating rule-like expressive power into standard DLs. They are also one of the most recently introduced DL features, and in spite of many works on algorithms and implementations, almost nothing is known about their computational complexity and expressivity. We close this gap by providing a comprehensive analysis of the reasoning complexities of a wide range of DLs—from EL to SROIQ—extended with nominal schemas. Both combinedand data complexities increase by one exponential in most cases, with the one previously known case of SROIQ being the main exception. Our proofs employ general modeling techniques that exploit the power of nominal schemas to succinctly represent many axioms, and which can also be applied to study DLs beyond those we consider. To further improve our understanding of nominal schemas, we also investigate their semantics, traditionally based on finite grounding, and show that it can be extended to infinite sets of individuals without affecting reasoning complexities. We argue that this might be a more suitable semantics when considering entailments of axioms with nominal schemas.

We study learning of description logic TBoxes in Angluin et al.’s framework of exact learning via queries. We admit entailment queries (“is a given subsumption entailed by the target TBox?”) and equivalence queries (“is a given TBox equivalent to the target TBox?”), assuming that the signature and logic of the target TBox are known. We present three main results: (1) TBoxes formulated in DL-Lite with role inclusions and composite concepts on the right-hand side of concept inclusions can be learned in polynomial time; (2) EL TBoxes with only concept names on the right-hand side of concept inclusions can be learned in polynomial time; and (3) EL TBoxes cannot be learned in polynomial time. It follows that non-polynomial time learnability of EL TBoxes is caused by the interaction between existential restrictions on the right and left-hand sides of concept inclusions. We also show that neither entailment nor equivalence queries alone are sufficient in cases (1) and (2) above.

We study finite model reasoning in expressive Horn description logics (DLs), starting with a reduction of finite ABox consistency to unrestricted ABox consistency. The reduction relies on reversing certain cycles in the TBox, an approach that originated in database theory, was later adapted to the inexpressive DL DL-Lite_F , and is shown here to extend to the expressive Horn DL Horn-ALCFI . The model construction used to establish correctness makes the structure of finite models more explicit than existing approaches to finite model reasoning in expressive DLs that rely on solving systems of inequations over the integers. Since the reduction incurs an exponential blow-up, we then develop a dedicated consequence-based algorithm for finite ABox consistency in Horn-ALCFI that implements the reduction on-the-fly rather than executing it up-front. The algorithm has optimal worst-case complexity and provides a promising foundation for implementations. We next show that our approach can be adapted to finite (positive existential) query answering relative to Horn-ALCFI TBoxes, proving that this problem is EXPTIME-complete in combined complexity and PTIME-complete in data complexity. For finite satisfiability and subsumption, we also show that our techniques extend to Horn-SHIQ.

We study branching-time temporal description logics (BTDLs) based on the temporal logic CTL in the presence of rigid (time-invariant) roles and general TBoxes. There is evidence that, if full CTL is combined with the classical ALC in this way, reasoning becomes undecidable. In this paper, we begin by substantiating this claim, establishing undecidability for a fragment of this combination. In view of this negative result, we then investigate BTDLs that emerge from combining fragments of CTL with lightweight DLs from the EL and DL-Lite families. We show that even rather inexpressive BTDLs based on EL exhibit very high complexity. Most notably, we identify two convex fragments which are undecidable and hard for non-elementary time, respectively. For BTDLs based on DL-Lite-bool-N, we obtain tight complexity bounds that range from PSPACE to EXPTIME.

We tackle a long-standing open research problem and prove the decidability of query answering under the stable model semantics for guarded existential rules, where rule bodies may contain negated atoms, and provide complexity results. The results extend to guarded Datalog+/- with negation, and thus provide a natural and decidable stable model semantics to description logics such as ELHI and DL-LiteR.

In Description Logic (DL) knowledge bases (KBs) information is typically captured by crisp concepts. For many applications, querying the KB by crisp query concepts is too restrictive. A controlled way of gradually relaxing a query concept can be achieved by the use of concept similarity measures. In this paper we formalize the task of instance query answering for crisp DL KBs using concepts relaxed by concept similarity measures. We investigate computation algorithms for this task in the DL EL, their complexity and properties for the employed similarity measure regarding whether unfoldable or general TBoxes are used.